What primary indicator is needed to stop training according to the guidelines?

The primary indicator needed to stop training is the model rating being at least 'Good.' This benchmark signifies that the model has reached a level of performance that is sufficient for practical application. By designating a performance threshold such as 'Good,' it provides a clear and straightforward criterion for evaluating whether further training is necessary or if the model is ready for deployment. This is crucial because it ensures that resources are not wasted on prolonged training when a competent model has already been achieved.

In the context of machine learning, there is often a push to optimize and enhance model performance, but having a solid baseline rating like 'Good' indicates that the training process has effectively produced a model that meets the expectations for usability and effectiveness. Having a performance rating system also helps in standardizing evaluations across different models and projects, enabling consistent decision-making based on established metrics.